Our students are capable of much more than we often give them credit for, and we can do more with them than we think. With the proper framework to initially get things off the ground, they can be doing authentic data science in their first semester.
while loop to utilize an index in the URL to scrape monthly data tablesjoin operation adds each monthly table to the mastergather()select(), filter(), group_by(), summarise()ggplot() graphics
filter(), group_by(), summarise(), mutate()ggplot() graphics exploring relationships among ticket sales, genre, year, studio, etcselect(), filter(), group_by(), arrange(), mutate()gather() for plottingggplot() graphics showing monthly win percentages throughout season for each teamfor loop to iterate over list then create and store ggplot() graphic for each champion in a new listparty::ctree() to build competing models based on recursive partitioning
select(), group_by(), summarise(), mutate()USMap() choropleths for comparisons among statesggplot() graph represents association between physical & non-physical crime per capita by state